class: center, middle, inverse, title-slide # Trading Analysis in Turkey ## Rsızlar ### Mef University ### 2020/12/26 --- class: inverse, center, middle # Table of Contents * Our Goals * About Trading Dataset * Line Graph * Mapping * Reporting Part * Thanks for Listening --- class: inverse, center, middle # Goals Our goal is to achieve logical results by using monthly import and export data between 2013 and 2020 by visualizing and analyzing their distribution by cities for Turkey. In addition, we aimed to reach the balance between export and import figures. --- class: inverse, center, middle # About Dataset In order to create the date variable in the dataset we used, we created values from 1 to 12 for the months in the "Month" variable in the dataset and created a new date format. Thus, we were able to reach the increase and decrease in Import and Export by date. Since we encountered a Turkish character problem, we fixed the errors in these parts. --- class: inverse, center, middle # Line Graph When we visualized the import and export figures by months of the last two years, we observed that the difference was at least in November 2018 and at most in August 2020. While the period with the highest import figures is September 2020, the period with the highest export figures is May 2019. --- class: inverse, center, middle
--- class: inverse, center, middle # Mapping We used the map method in order to examine the Import and Export figures according to the provinces in more detail. In this way, by clicking on the cities, you can better understand the distribution between Export and Import over the years and access its details. --- class: inverse, center, middle
--- class: inverse, center, middle # Reporting Parts When we examined the Import and Export figures by years, we observed that the Marmara region is at the highest level every year. --- class: inverse, center, middle ``` ## # A tibble: 83 x 7 ## # Groups: City [83] ## City Export Pop MenPop WomenPop ExportPP WomenRatio ## <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> ## 1 ISTANBUL 88827639699 15519267 7790256 7729011 5724. 0.5 ## 2 SAKARYA 5351062246 1029650 516000 513650 5197. 0.5 ## 3 KOCAELI 9917082987 1953035 988098 964937 5078. 0.49 ## 4 GAZIANTEP 7811872038 2069364 1044799 1024565 3775. 0.5 ## 5 BURSA 10898036437 3056120 1530956 1525164 3566. 0.5 ## 6 CORUM 1539822551 530864 263354 267510 2901. 0.5 ## 7 IZMIR 12168871669 4367251 2174319 2192932 2786. 0.5 ## 8 DENIZLI 2883700528 1037208 517716 519492 2780. 0.5 ## 9 HATAY 3063173877 1628894 817998 810896 1881. 0.5 ## 10 TEKIRDAG 1948238746 1055412 542646 512766 1846. 0.49 ## # ... with 73 more rows ``` Above table gives 2019 Trading figures sorted by Export amount per Person for each city. First 5 cities have huge industry operations and their Export metrics are better than other cities. --- class: inverse, center, middle # Thanks for Listening